title: Target prediction for an open access set of compounds active against Mycobacterium tuberculosis.
abstract: Mycobacterium tuberculosis, the causative agent of tuberculosis (TB), infects an estimated two billion people worldwide and is the leading cause of mortality due to infectious disease. The development of new anti-TB therapeutics is required, because of the emergence of multi-drug resistance strains as well as co-infection with other pathogens, especially HIV. Recently, the pharmaceutical company GlaxoSmithKline published the results of a high-throughput screen (HTS) of their two million compound library for anti-mycobacterial phenotypes. The screen revealed 776 compounds with significant activity against the M. tuberculosis H37Rv strain, including a subset of 177 prioritized compounds with high potency and low in vitro cytotoxicity. The next major challenge is the identification of the target proteins. Here, we use a computational approach that integrates historical bioassay data, chemical properties and structural comparisons of selected compounds to propose their potential targets in M. tuberculosis. We predicted 139 target--compound links, providing a necessary basis for further studies to characterize the mode of action of these compounds. The results from our analysis, including the predicted structural models, are available to the wider scientific community in the open source mode, to encourage further development of novel TB therapeutics.
authors.affiliation: Genome Biology Group, Centre Nacional d'Anàlisi Genòmica (CNAG), Barcelona, Spain ; Gene Regulation Stem Cells and Cancer Program, Centre for Genomic Regulation (CRG), Barcelona, Spain.
authors.forename: Francisco
authors.initials: F
authors.lastname: Martínez-Jiménez
authors.forename: George
authors.initials: G
authors.lastname: Papadatos
authors.forename: Lun
authors.initials: L
authors.lastname: Yang
authors.forename: Iain M
authors.initials: IM
authors.lastname: Wallace
authors.forename: Vinod
authors.initials: V
authors.lastname: Kumar
authors.forename: Ursula
authors.initials: U
authors.lastname: Pieper
authors.forename: Andrej
authors.initials: A
authors.lastname: Sali
authors.forename: James R
authors.initials: JR
authors.lastname: Brown
authors.forename: John P
authors.initials: JP
authors.lastname: Overington
authors.forename: Marc A
authors.initials: MA
authors.lastname: Marti-Renom
mesh_terms: D000595:Amino Acid Sequence; D000995:Antitubercular Agents / Q000737:chemistry* / Q000378:metabolism; D001426:Bacterial Proteins / Q000737:chemistry* / Q000378:metabolism; D019295:Computational Biology / Q000379:methods*; D062126:Databases, Chemical; D055808:Drug Discovery / Q000379:methods*; D062105:Molecular Docking Simulation; D008969:Molecular Sequence Data; D009169:Mycobacterium tuberculosis / Q000737:chemistry*; D011487:Protein Conformation; D016415:Sequence Alignment
chemical_list: D000995:Antitubercular Agents; D001426:Bacterial Proteins